Repeatability of computed tomography liver radiomic features in a nonhuman primate model of diet-induced steatosis

Hui Wang; Jeffrey M. Solomon; Syed M. S. Reza; Hee-Jeong Yang; Winston T. Chu; Ian Crozier; Philip J. Sayre; Byeong Y. Lee; Venkatesh Mani; Thomas C. Friedrich; David H. O’Connor; Gabriella Worwa; Jens H. Kuhn; Claudia Calcagno; Marcelo A. Castro

doi:10.1117/1.JMI.10.6.066004

8 December 2023 Repeatability of computed tomography liver radiomic features in a nonhuman primate model of diet-induced steatosis

Hui Wang, Jeffrey M. Solomon, Syed M. S. Reza, Hee-Jeong Yang, Winston T. Chu, Ian Crozier, Philip J. Sayre, Byeong Y. Lee, Venkatesh Mani, Thomas C. Friedrich, David H. O’Connor, Gabriella Worwa, Jens H. Kuhn, Claudia Calcagno, Marcelo A. Castro

Author Affiliations +

Journal of Medical Imaging, Vol. 10, Issue 6, 066004 (December 2023). https://doi.org/10.1117/1.JMI.10.6.066004

Abstract

Purpose

We describe a method to identify repeatable liver computed tomography (CT) radiomic features, suitable for detection of steatosis, in nonhuman primates. Criteria used for feature selection exclude nonrepeatable features and may be useful to improve the performance and robustness of radiomics-based predictive models.

Approach

Six crab-eating macaques were equally assigned to two experimental groups, fed regular chow or an atherogenic diet. High-resolution CT images were acquired over several days for each macaque. First-order and second-order radiomic features were extracted from six regions in the liver parenchyma, either with or without liver-to-spleen intensity normalization from images reconstructed using either a standard (B-filter) or a bone-enhanced (D-filter) kernel. Intrasubject repeatability of each feature was assessed using a paired t-test for all scans and the minimum p-value was identified for each macaque. Repeatable features were defined as having a minimum p-value among all macaques above the significance level after Bonferroni’s correction. Features showing a significant difference with respect to diet group were identified using a two-sample t-test.

Results

A list of repeatable features was generated for each type of image. The largest number of repeatable features was achieved from spleen-normalized D-filtered images, which also produced the largest number of second-order radiomic features that were repeatable and different between diet groups.

Conclusions

Repeatability depends on reconstruction kernel and normalization. Features were quantified and ranked based on their repeatability. Features to be excluded for more robust models were identified. Features that were repeatable but different between diet groups were also identified.

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Hui Wang, Jeffrey M. Solomon, Syed M. S. Reza, Hee-Jeong Yang, Winston T. Chu, Ian Crozier, Philip J. Sayre, Byeong Y. Lee, Venkatesh Mani, Thomas C. Friedrich, David H. O’Connor, Gabriella Worwa, Jens H. Kuhn, Claudia Calcagno, and Marcelo A. Castro "Repeatability of computed tomography liver radiomic features in a nonhuman primate model of diet-induced steatosis," Journal of Medical Imaging 10(6), 066004 (8 December 2023). https://doi.org/10.1117/1.JMI.10.6.066004

Received: 6 July 2023; Accepted: 20 November 2023; Published: 8 December 2023

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KEYWORDS

Radiomics

Liver

Computed tomography

Cooccurrence matrices

Attenuation

Diseases and disorders

Feature extraction

Purpose

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Results

Conclusions

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